- [Instructor] The Google Agent Development Kit
or Google ADK is an open source framework
for developing and deploying AI agents.
It was built by the Google team
with flexibility and modularity in mind,
and provides a comprehensive toolkit
for orchestrating complex AI behaviors.
It's also particularly powerful for building systems
where multiple agents collaborate,
a setup popularly referred to as a multi-agent system.
ADK is a code-first framework that comes in two flavors,
primarily Python,
and there's also support for Java.
Support for other languages, while not promised,
is assumed to be on the way
as the framework receives more adoption.
Now that we know what the Google ADK is,
let's check out some of its key features and advantages.
The ADK comes bundled with a suite of features
that empower developers to build sophisticated AI agents
with great efficiency,
ranging from structured component design
to robust tool integration and memory management.
The first feature of the ADK
that we'll be looking at is modularity and composition.
This is the ability of the ADK framework
to enable the reusability
of independent models like agents and tools.
This modularity allows developers
to break down complex problems into manageable pieces
and compose them into sophisticated
LLM-powered workflows and agent hierarchies.
The next feature is the ADK's tooling
and action-taking capabilities.
Agents built with the Google ADK
can effectively perform actions
in their surrounding digital environment
by integrating a wide variety of external tools.
These integrations include APIs, custom functions,
and even other agents.
This enables the agents
to perform actions like sending emails or Slack messages,
browsing the web, and even executing code.
Then we have state, session,
and memory management.
The Google ADK comes with robust systems
for managing your agent's state and memory
across all interactions within the workflows.
This ensures that agents can maintain context,
recall previous conversations,
and also learn from past experiences,
thus leading to more coherent
and intelligent interactions.
Another feature of the ADK is the flexibility
of orchestration and workflows.
The ADK supports defining structured workflows
for sequential, parallel, or looping operations,
as well as dynamic LLM-driven orchestration.
This flexibility allows developers
to design predictable agentic behaviors for critical tasks,
while also supporting adaptive decision-making.
Another major selling point
of the Google ADK is its integrated developer experience.
The kit comes bundled with a powerful CLI,
and also a web interface
for development, testing, and debugging.
This integrated experience significantly simplifies
the process of building, iterating on,
and troubleshooting agents.
Then we have the streamlined deployment options
that provides clear pathways
for taking agents from development
to production environments.
This includes options for containerization,
as well as direct integration
with Google Cloud services like Vertex AI Agent Engine.
And finally, the model agnostic design
of the framework itself.
While the Google ADK has been optimized for working
with Google's Gemini models, it is largely model-agnostic.
This means that developers can, with some integration,
use other LLMs from OpenAI, Anthropic, and so on.
The ADK is built to be production-ready
and provides the necessary scaffolding
and runtime environment
that improves the developer experience significantly
compared to working with plain LLM APIs.
It includes the structured environment, tools,
and memory management layers necessary for the LLM
to become a truly autonomous
and functional agent capable of complex operations.
Some practical use cases of the ADK include
building customer service automation
that routes queries to specialized subagents,
developing intelligent document processing for extracting
and acting on information,
building personalized digital assistants
that can plan simple to complex itineraries,
or manage shadows.
It is also ideal for building decision support systems
that synthesize information from various sources.
So that's the Google ADK at a glance,
and in this section,
I'll be guiding you through setting up
your first ADK project
and building your very first agent.
We'll also be adding tools
and testing out our agent in the ADK web UI.
So if that sounds exciting to you,
let's get started building our first ADK agent
in the next video.